Semantic Networks and Associative Databases: Two Approaches to Knowledge Representation and Reasoning

Two models, one originating from an artificial-intelligence paradigm and the other from database research, that incorporate connectionist techniques into their knowledge representation and reasoning processes are described. The first approach, called evidential reasoning, is based on semantic networ...

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Bibliographic Details
Main Authors: LIM, Ee Peng, CHERKASSY, Vladimir
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 1992
Subjects:
Online Access:https://ink.library.smu.edu.sg/sis_research/109
https://doi.org/10.1109/64.153462
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Institution: Singapore Management University
Language: English
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Summary:Two models, one originating from an artificial-intelligence paradigm and the other from database research, that incorporate connectionist techniques into their knowledge representation and reasoning processes are described. The first approach, called evidential reasoning, is based on semantic networks and focuses on solving inheritance and recognition queries using a rich internal structure. The second approach, called the associative relational database, provides a query language to manipulate knowledge stored in simple uniform structures. In addition to solving ordinary information retrieval, associative databases support robust retrieval with imprecise queries, which is impossible in traditional databases. The two modeling techniques are compared.